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In this Project, you'll scrape a novel from the website Project Gutenberg (which contains a large corpus of books) using the Python package `requests`. Then you'll extract words from this web data using `BeautifulSoup`. Finally, we'll dive into analyzing the distribution of words using the Natural Language ToolKit (`nltk`). The natural language processing tools used here apply to much of the data that data scientists encounter as a vast proportion of the world's data is unstructured data and includes a great deal of text. To complete this Project, you need to know how to import web data into Python and how to work with natural language text.
- 1Tools for text processing
- 2Request Moby Dick
- 3Get the text from the HTML
- 4Extract the words
- 5Make the words lowercase
- 6Load in stop words
- 7Remove stop words in Moby Dick
- 8We have the answer
- 9The most common word
Data Scientist at DataCamp
Hugo is a data scientist, educator, writer and podcaster at DataCamp. His main interests are promoting data & AI literacy, helping to spread data skills through organizations and society and doing amateur stand up comedy in NYC. If you want to know what he likes to talk about, definitely check out DataFramed, the DataCamp podcast, which he hosts and produces: https://www.datacamp.com/community/podcast
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